Lab 6: Saliva Practical

1
Lab 6 Saliva Practical

• Beer-Lambert Law

2
This session.

• Overview of the practical
• Statistical analysis.
• Take a look at an example control chart

3
The Practical

• Determine the thiocyanate (SCN-) in a sample of
  your saliva using a colourimetric method of
  analysis
• Calibration curve to determine the SCN- of the
  unknowns
• This was ALL completed in the practical class
• Some of your absorbance values may have been
  higher than the absorbance values of your top
  standards is this a problem????

4
Types of data
QUALITATIVE Non numerical i.e what is
present? QUANTITATIVE Numerical i.e. How much
is present?
5
Beer-Lambert Law

• Beers Law states that absorbance is proportional
  to concentration over a certain concentration
  range
• A ?cl
• A absorbance
• ? molar extinction coefficient (M-1 cm-1 or
  mol-1 L cm-1)
• c concentration (M or mol L-1)
• l path length (cm) (width of cuvette)

6
Beer-Lambert Law

• Beers law is valid at low concentrations, but
  breaks down at higher concentrations
• For linearity, A lt 1

1



7
Beer-Lambert Law

• If your unknown has a higher concentration than
  your highest standard, you have to ASSUME that
  linearity still holds (NOT GOOD for quantitative
  analysis)
• Unknowns should ideally fall within the standard
  range

8
Quantitative Analysis

• A lt 1
• If A gt 1
• Dilute the sample
• Use a narrower cuvette
• (cuvettes are usually 1 mm, 1 cm or 10 cm)
• Plot the data (A v C) to produce a calibration
  curve
• Obtain equation of straight line (ymx) from line
  of best fit
• Use equation to calculate the concentration of
  the unknown(s)

9
Quantitative Analysis
10
Statistical Analysis
11
Mean
The mean provides us with a typical value which
is representative of a distribution
Mean the sum (å) of all the observations the
number (N) of observations
12
Normal Distribution
13
Mean and Standard Deviation
MEAN
14
Standard Deviation

• Measures the variation of the samples
• Population std (?)
• Sample std (s)
• ? v(?(xiµ)2/n)
• s v(?(xiµ)2/(n-1))

15
? or s?

• In forensic analysis, the rule of thumb is
• If n gt 15 use ?
• If n lt 15 use s

16
Absolute Error and Error

• Absolute Error
• Experimental value True Value
• Error
• Experimental value True Value x 100
• True value

17
Confidence limits
1 ? 68 2 ? 95 2.5 ? 98 3 ?
99.7
18
Control Data

• Work out the mean and standard deviation of the
  control data
• Use only 1 value per group
• Which std is it? ? or s?
• This will tell us how precise your work is in the
  lab

19
Control Data

• Calculate the Absolute Error and the Error
• True value of SCN in the control 2.0 x 103
  M
• This will tell us how accurately you work, and
  hence how good your calibration is!!!

20
Control Data

• Plot a Control Chart for the control data

2 ?
2.5 ?
21
Significance

• Divide the data into six groups
• Smokers
• Non-smokers
• Male
• Female
• Meat-eaters
• Rabbits
• Work out the mean and std for each group (? or
  s?)

22
Significance

• Plot the values on a bar chart
• Add error bars (y-axis)
• at the 95 confidence limit 2.0 ?

23
Significance
24
Identifying Significance

• In the most simplistic terms
• If there is no overlap of error bars between two
  groups, you can be fairly sure the difference in
  means is significant